Risky business

Abstract

The growth in the gig economy and a preference for home delivery of meals due to COVID-19 have led to huge growth in the food delivery business internationally and consequent road safety concerns. There is increasing evidence that delivery riding is an occupation with significant road safety risks because work pressures encourage risky behaviours. However, there is little or no research that directly compares delivery and private riders. Thus, the aim of this study was to examine the impact of riding for work by comparing the observable riding behaviours of food delivery and private bicycle riders. Specifically, this investigation used decision trees to analyse the prevalence and patterns of risky riding behaviours of 2274 bicycle food delivery riders (BFDRs) and 1127 private bicycle riders observed in the inner suburbs of Brisbane, Australia. The results showed that helmet use was higher for BFDRs than private riders (99.8% versus 93.4%) but varied by company and for some companies, female BFDRs had lower wearing rates. Male BFDRs on electric bikes were more likely to wear helmets than those on standard bikes (99.7% versus 94.9%). Using a handheld mobile phone or having a mobile phone in a cradle was less common for one company (0.6%) than for the others (3.0%) or among private riders (1.8%). Among riders from the Other Companies, using a handheld mobile phone was more common on standard bikes and differed by time of day. Female BFDRs were more likely to be observed using handheld mobile phones. Overall, 24.0% of riders facing a red traffic or pedestrian signal (“red light”) did not stop. This was more common among riders who rode on the footpath (Australian term for sidewalk), and particularly those who moved between the footpath and the road on electric bikes (49.5%) and among those who rode in the wrong direction in the traffic lane (55.0%). Whether the rider was a BFDR or private rider had little influence on red light running. The results suggest that BFDRs are not more likely to perform the risky behaviours examined, but that other factors such as bicycle type, gender, time of day and infrastructure appear to be more important determinants. However, the differences among companies suggest that organisational factors deserve further investigation.